{"id":63,"date":"2026-10-15T05:44:02","date_gmt":"2026-10-15T05:44:02","guid":{"rendered":"https:\/\/therisk.global\/risk-management\/?page_id=63"},"modified":"2026-10-17T10:19:23","modified_gmt":"2026-10-17T10:19:23","slug":"methods","status":"publish","type":"page","link":"https:\/\/therisk.global\/risk-management\/research\/methods\/","title":{"rendered":"Methods and uncertainty"},"content":{"rendered":"\n<!-- Nexus network page \u00b7 https:\/\/therisk.global\/risk-management\/research\/methods\/ \u00b7 source template \u00b7 generated by integrations\/wordpress\/network\/build.mjs, never edit this file --><script type=\"application\/json\" class=\"_iub_cs_skip\" id=\"nxe-water-data\" 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e3x4M069tS3BzIzBVXJvzqDn0uXGZmc2makcmXWfFsK3fH1NeO9OtBFpv63pV+r7xGJN8iefI2JW8qISAPtNukR+k853YC+TWwLCGeUkMIJYdZHUMUxtZUV\/j0nbrwFs+Qv+\/j\/HBo9Wc6gMHdXd4k0tBwpd521oD4uevMwLG2Wtd+4yAq3rWO9cB4oPvP+BiS0TEI3VvzgRP3Bka1stS+Ogo44vU8aJrqM\/4gBxHM1wepq2I\/AUfn9lFXJ7O0Q8MCZWjYCDKwnxZinNlFR41F94NtVBMX5iS6rDzmwpMaoAFuj1V1RRw6KhzKY8B1xj1yrajD1xk46Aa3GI3FaNekahnc6Aa43BbGSuFrRD4eimZx4yE6J4\/tVOFLd3LpVx170gWICZCactK7ceFUGq4n9BfbL+pvKBcFXf+I1qlV8EmYMDrNiryQeL2KUWKWnq1n3j4j3hUzd9oY4aJb+ttHcRrivYE5\/AQr1HGs4Dllf7gq9uUwAFpzVtrY5roe4j6+jdvamPQarBnNmnkfjLvSkqjus+3p7UbtaN7W3POOfCePMKsbMeji6T\/g9g35fyp5kF40hl5mIAKbZPeh\/mB700kW1L+jNVc+iFsMdx0LoeajrR39\/ljPEr0uJT0GM2bo6nXjyBSLUaCeHlB7DtAuNYWOCAjPIvPV74mVC7ZacsEYrC4cftqleAwCinqcnDPCpuWPKn9MLpLTFSoskjRvU5tdIW12hWY0brC7jJgOIWU6lJoRFRCjEYjRRmkOVN6RfZ\/yixoc6zaTYGTeeJ3lpjczXtY\/\/\/4ZvuMToTbwVy8Q5Le0Ks+3wfx3oIQD\/CsC\/T8\/B5e39c+mHF60D1y6pp8c+Ms1r+HN+nSj3sOJuj7blLnR\/ulLX\/kSMDZJ1\/+JwkamYHFDSCrwSubXmqcSUJ+6QHIbTUfSbvFQ0BF2k79rOt5PDaPUl6uZo4BOUKBra6LGtAgy7MASvS7Rtj3XhjPgGCUX2xvITISTwQ3tZZXhELs2TE2whgxBaQGKTxqzhgzJkii3XtdRy9C3ES\/cCl4gaD47G8Ydd8ITdCawA3nBxJKfYqDUucrJIyQZ3URuEY4962pp6FXVWmyDcHwtutxS\/UqEliL5k+AKG4bTqaJmZWrSWyBPb7V5OadNJhNOpqgQvsHh+yok2xbSBsawfNHWjqV7w7OUJDe8ugsUyzEErM6kfkz2fjCZn0xvGKNUMd2DZC1VdkBhVzkSDwjPnwoy+6kWai45fJPoEFye0dGEpI\/UKZZlG9VUIMg8f5n+QHX3a9QHen6P0h5omI9SHiiYc3QHZ77yQPUkYWCC9uAc5mkDFPjhTGNSvGprAyNgBR0jmBrTGRRVeYGS\/fwv7ZOHbtj\/BJt\/qEBW1B+yY\/vJLNq0nmQLzelvya6V8Ql\/1iR1d+4kGXFwdXfvTLgfq\/2zfS3Yw741a8nFbewv5XIsYNlGXgb3L+AZVA2QbPD\/kl9r4z+Rx7OSg\/8NnM39rH7Z8cz2+GtOaG6WjzqkObDezCOD\/fwjNhkOM5aJmLj9QVTaXYkQqMZ\/w+6mm6k+NA3cc6mdIAglVUc5EbrU5zhJCLmeggD78NewabLiWO+Np\/jFtp82T3Vttf\/nPj0k1bvW0ki3nfwOrcXz+qDFJz1ha1pfdqH+mCQb8xHDknIMbwaq3MeNZXJ\/Mx17mufTLKjTN+7+QU+6DeZ0qy812xJhblrv1R7IstsAGsIMOQjhiPf10O9I\/9ohnLMU7B36Rvu7tMyz8iafpF7vc3qMdHzkyIdoVbPLd5mz9V+J08re8GjnECew6FQDOO2PNSuwo\/fvFLPuH+4KGp+XxdKRndliamnr0Ob\/MOELLJp61FuIweefiSPh9ymXP0nem1HQeJ26pCQnmF9mZ8Ntk5ckZdPAZCwZrtvlyRXTwS5Mw075PvVIqi\/v3wVfwh4XdZPFz+9t5pyBEF3GX01STUQVccBExD\/KU3Jsat9YG+8clzwxkKxr6Yc7fjPBuJn9GRkfzTaHb++lod5CdOmVrKhhY1iGaeMcioKjGj8uzWHNKNnR9cTX7HDVzjdkKV6zBH5nLM+KKx3+O5XDy3ectqZjGgrnwQQc0YUdokRltAC+gmNuJhcHEByoG0VQVYjmPMNTj68oE0hKc4zFFmh8n8XImU34vttxDw6IoHs+5u+X020IDhD74sMYuT6+OF0LGkmMdiPmHXTrX0p0IYqbNYaEbma58cnuzpWALmXVzEEo7UMrTHC6K3KbLI90EDtTh0C0YGFyhOSmW7U4bB\/DmEMJKbvGbmSpqN2zU4\/qnKEb8wv+9YxXaH6khAiqX\/Z5wSIjgJKygEuiRzpwZ\/Mlg4vQLkG6Y0yQT5ObEagWY5F8\/qCps8AWLwg3JhhndSbwNzgj6q+DG5kRSI7doKa9L2muEpVvqoi9j+SxDTh+fOAZ1yFe9sVU1ROTag6s7CNnqXp0J+1OOoPJBFCjBwlaf2326c+FLkHPfexf2sX9KOk2oxotM5YODvtRIT6Mnaz0yRNqnIeYJUmEAcn5RzmhTcMtEF61qcOTyomuuh\/iBLh0Q+KvZRx5ARstMKQC3u461iammxXPZlmMxICqSLbXBM8lUme\/d0D3Rdl87uLqv6972hPHxox3cC68pye0VTb3AXilXDrHUdd\/pZwf67aInCoNqdNiVDanGX2RbfABwOXoG3n1lRsB8Yo13OCOMXSRjvDy9cl++j70YCYQmxascz0XjiODgzN2zoXkyiA53gJIngwSxtxcSL4MkhcugBTIIGGKmgtpK4O0XYLxUAYpXILxnQzSbgnGbUtKUNYSnNv2CHEugSUndHcJ3m0pqdveEszbUmK3fV3c80LWTIdwe4tb3fke4fceecQqsOg0IZ+yk0RNhk3820nQRzfjrEizImugkOKogsk1hkk7XmR9R3\/L\/HoXV\/OmkyFjwZIeNA5uGEFjUp5BVjCZ1JLRTGqJXiY1GvJ3yqNYTLs\/nVBHDks3HT62KpME3+iin0rm43IXQOr4nYSO30n4tEkKQXJs+Hwec+XoNW+F5H0R72ydqx\/xezrR0x3I0sILH2HV\/r0vmhOpo\/HZXfP3CclI8TMROgkDpi9uHFW5uuwMjnA+UQQWW55xXIwWxqYdw6s\/51FNkB7zaJz8CzTrvGy08oj0b3esOUVpMhqUoBGCBOWvlme\/4Ks93VdzvL\/iQCEUfYYwhTf\/5LAlbOaf0fGHDJ7G\/\/0\/xn+Gb9fa+Cc0lOr96TCWriRsy9Xcn01CWWruUfeMk2gxMhIBzs1XLI+kyg+A9FlSv0mvKCf1BbWjmTtaDYPOjyu8wkRizmEt\/+58UMikRZlntmM79FgBlCLi6xNoclB3Hni0CQmld0Q\/B8l9EsqsjX4O3PLvVyFAPwfZQrfZJX1\/0\/2LkqStDwq7rewTO+g+6ffafmVt0c+BNxDvV1aMfvADYB6viND3TjjuVsPjZTRRJYcrG\/8jx5WboB8RV3jMlgJX1gb\/6GGpe1mKnxSgHwl+Ug\/93JUOU4kyKiXm\/18Y095YfBFs3ch0HhAXQ0dXpHdCi6uI6+lTuOikNr\/02qy+KGdS5gB22JQ8dhif6KPK06jB+8XyxjyyZw2x8\/pj8nKFkrLufNoB0WWR80xc7JooHSfrA8uMljvonVADe7a8\/roTzkQf9t4URqPCnS\/mCpNgb95eYbMx2aEOOU943cr78W4TU1G4wUshXiaZhjNvPSTppjxVjI2c99DpmxiPwlm1Rad7YNI1KZjRLNidElm+irtac0YLN6ksT7HFVsGbBQ\/5+dK6hRuwzJ9OLCUUPKeyauk4JKtiEkcmS4rLM5wdDYjU7LJmzpWNAQ9w0kfDmg2i16DoyoPqW8xJiMR2Qif8DQ99WgJ6fclfGBOma6Hf2zx3pmMtwYdexLusKLPFF2WuG1A1dw7gW5K9MIVGKT6vshCpwS9JjDHUhRPLO7uBLNPjHWMzkuYmZLu8Cx6bBpRX1N2H86W+\/46xT2chnU8Yg93MWd9471nvQZ2URf7eEp\/QRTizC033ZkxqKBLAcQTCsmQOzNbycRhApDR5FO3yHr7h\/JxCHs7D3NJ7uv3JHbU1XLETPdeJaaF5OFb8kZwe0zBaVbdEGQFB3kyXAFzSCUt5+xOoP3+jhX\/kxmz8ISQgWS8p9YnJGukK\/eA7q8n63pODHu5dZwQzb85mf+sDC2ZvOBVYofwDVmiWCnCjaWKsA5V2x1oM8xvRIWh9y5Olt1VK4gvMnEqFmk9g684+LyWV6q2uArtN6iFPpJ\/25AYMFEHImK2XB\/9MD5+uIm\/3w8c8TqOCkQb8pUXfvZkKVVW+1riMeT8dzEYHIWw2tOGUuFOykmXbnV+eig\/aa2\/jZvMrOjsvn1LXWTKz8Uu6uzRkJq2uqD\/Og0UloeYJZNruM7urkdzV820cQ5FqrvDzPO7J55JrFdetc3e8590Jo6eHra7QrPn9eN3mJXah0VLOdB47S9vAh0L81Wimo39nn533VItuH5vRUaSE7pnq5n3BiJgCz9SYsAOPDjXOYaaqRIM7S55Z8wNF5Cmh2E2r9fDXLq3Wy2Veeayvj41jaBikd4XT87QwycBxFsMZEEjJgevN\/eD4kNM1O2Lb+JNh2ofJm3hNjON+\/5CLx3dPbKoDvanSNAGaLD7M09lE8mTyuQo63Iejsuf9vwanw1HDUj5BHPLbwohGtg3DYd19Pszw2honbWWm3ftWRsMIKxAbxkH4cJOelKhpwTu8yyp6d7JcvXtoSozwg4UcR4CE3UyWWaa03ST1D0WZ32u3UDlMGyKkPsA+pekTS+5DfHJXRbQh8hcZDLbXd8aWCSdZO2QcIsdEj9EX1uvH2Z8es3RS2N9of1R6r0uwS5Bo+s5w8zTgE1+OYEEOm\/T2Brb3fohjwpx5aLojd5dn2N8Cz207TG3HmuVGlK0HWHMmJ4ithRNeq7oGZrS\/WEv5cmKR+fE+xqD+8LF2BCFbROk1QM8w3GVqP8vJlui+36SJzpcyWHRC3TEm6sLl8eOiVkU0ly6776Dv1fugg3ZJcYLEbmfjP1qLedVVRRZqPlE1NmgKIqIDnr3Sr144JZBrxeWN9qzHei8y6qw341CXA+2TPJ5B\/dyaH6fOPtpGsCFenOfs7XNWGHV1jOTvGa7PBQzwEQQHagTGv88QFl5tK8Sfx19vf3gXUuGK83\/vjz9LUsKNTzi3dDN0Z+YI+doTe4IDTtkFlfuBYjnd3YD1CdmmN\/gXkpRveIf0303SZJ4Na4V4oEEQtKF+n2eDxrkOx4UVnOWsZVgLaqg+NEBDFPzu8rLEU+\/uHzhSFKyxUyKmoghxuNs9xDi4+Vs4gDd\/e8KJ81jt727Jd6kK1NrRaLGBpng02V+mySxHAs9Q2lnJ2Plds5PbQEhJoA\/wmqLSQBYlTgTZF5N6axerjqsyzyNQ0f4h5FLZwp6kHzCu\/b6TtPre71g71nPr9ZQ1ELNu2E8aoeG+i2SG8nLQEx6KPacpcX3HPEa6ozKz9rCzAp8hmOuP1SxC8UBmUx6PtF7cfohzhJI1flBW3emQbmFUuglshQ+N6No0ZXEDlwsEFSji1kug3a5M2lafTx7MZm4dv3NbXoFdXm9jXHjgxAHn0CXgbeO\/9TFi\/NGhpl0hctTMuC3U7or4E14qWNcwGfwJH3vFOtb5jPSu+E0xu6uprrz3bb4uM\/LtN2EvKqRWa5Ba+4TEzp0WDHEAgoyM3YIXiIK6PW4ePQOdc\/rnx9x8z7qd+4bPh+7O7Bfde3KdcjdGP6dDnNuDu0SpjTlWdOi32nRKYg4Uu2fVmfXaTbsg32Cb+gbmMG5g8v3D8hqSfqproe5CbjV9TH9UNuVxo490AIbjTNl6+EwSrRBSgRh+n0QkZQjkpxpMpeFBXWTFsc\/FQ2X3Ib2vb3wv1hfH150BElG+z1smcTZUzgBUXgEd8HyyOVCfEJMZkgUNWYLYUr+gPo2W+rW+uM54td+JJLBkviQ87K59zIHan5Cohx7Ep+yymfWpwAIQiNuy1J8d7LIY7j1agIuy8YrgZGlENeSVnpRJvqfvIiJQYUHApEdZFLc1VgBAO\/qAKIDsm6CCANVAImYmct4+GU\/oJQz4iXGrwDIEUs7JX85j4t0kxz\/Rz\/FQ0Qj3Bm4Q3Xn+cq2bLH1HJ0Dadn+\/wj4ljlDDIi1T44JFMugqjxgO5yRDxoJ+ffRcR3S2x9oRJcStF0wjpeSehjHJtLT8NFCtff8toUgSEjr8ufhujrlAAEkG8sGyH2dVnEMDtPcAl7fpKwTB3v8FlZvG2dL+hHc02daSyzC+c5jn2aWGxtb6ZITWJzSK0P9kONanTXsn\/Y9IMmF621qf2OuthwGlBALfV5bxRoydifx5rKqAOiGPc\/BeXhshKxsXq+gviYxVdDAdCDoqPpxhcyqTmj9Muii1sa9yJGFVN5T3oKsANGaQsRZGhai7RoExSw9A5sQi2SfZQ24wHz0gzVY7YBMlbNMbMnK0XzJu26PzFLTBIBM3QnxZJqWA2E2luJGh0Icu45PYx1brGtLkWdJQHbVpY13rZ28W1zOssnhvNCBCxSFRQz0xE+zULaF95MylDhVkEYIiejRCwZQZTHi7oOuPVrE+0HlAcb8kxTKXjXVi1FWZK0NIhIQWfGEzf6KDYyk3RMsIuYsr\/QXGWU9pnZXcJ0xOsw0+Gwc6HFUH6jn+Fe39f\/tsoiOZWdb2E5R1VljYTQ9E+nhyvCSeC6fep7scoDqS3L6bxYSGWF+nRnK7ZqPxJadFTu07tfo3MaZjed+IjuWjx0No695RtRRK2TYoOtRg+dzwMO0sGxNFdsIucC9vWni6+zrAETP4eFPSjgnqLIFc3T0ZK+t0gd6HCN\/KIh1QoX8wPcWgKIuZvJNJUoRuwcK5+VbFS76P58VqNxupcCLj0JoH4qad42JOhheG7IONzpssoWpFnqpiOhVqd+Aq7mwooVlHTNaRZHkNY1JZGJiQzvUvu+fkO4oInnzlSypRl0WC\/z1P6m0xBPW3txbg5TsX3v+NJHcrnufE+SNRbo5UrTkEinlK3QJ632yHdtGn0jSRu2Hky\/8CK1IdvTWSoQwwapc2vd2llh90p49kcqOp2tNmBBubu3A5sS\/VJ\/ayAU8em4uGThHFyCQOs09apNQP47jdHRAvAUqltWjJ0tL9zvjDyDOtfNDCp7q+c\/KvB16wQALAh5UZweYVwmLI4HFgU5VYC6wOEwHkcxjR+JQpMhvlMv9e\/GN81MpzWvHZPcxhajSTbEB3XB+x8\/vkHIv0wymgmggY3l+gOywvybJA6aL1aE2mPm\/19XE1smCkJMwCqXEqDVJXcQjEz8P1KZV5aUHyKjlI4w8El09YMHYTm32MSXo93t+3\/jBie1B+MesgSrJqJPB1Zi4DZFFk0hlgyzK++pmyLLvMWYWufUlteecXHlrMIcLHxsmtZO2I53CrJKsIIcZlXuMadMwiLMNx+5eN\/O426LKqQ7xiybFpS6Fjt2u\/YVtrUNRrVvXezUjLLbim+lMrJR7swRxc4yQEnECFFbokq4jjG4Z7PbdCk69nl0eQn28PsVBYngQt8xJy90N6EZNnCTb1+VHiNIF+EwU1JpEi+kN0TVDnINVc5GXSWztupajWvcPKZWNpvjCkNZd6wXaUm60fAbP95gyH3bfzZEZmBN+mznxp998+QBqUo32p77VCCNnaCtNVO4rNx7BrzIgt2qeJU8tCeeZadrlZj1u+ZoX2jh1PsTPFQCVJYn7eKQtP4l1ji3xTSaUjAjDKNTSZUxQdV7aEMU8W\/6DzznlWZ3sm1sNLBZvmfWRcl9tk7YxQfl0bjN1hy0cVoKos2qNq40I348gcKS+nMmAGljXa3x9Gl\/uWMsB82ckyYzOFXqYzUHLhciNTYpIBjbxzcm8UAiOQo4ihCYdhrO+Z0VFSk7urTCSpWT8WL8V5QWv13UiroFNEIpFNFJVU9OqmcreC2kVTyXf6Fal9LBHo1KVm\/MH54X1x\/XvZ2vRMFNwJkycJ+LhpiKHU66NJnj\/WE+3rUwKOT7w\/Wn\/Yufc6oknhf2Md7+SZ0nYf2W+7RJO506yPH8QDArZV\/S4q48EkLrekoVN3+\/Oq3BX5dZKWrfiYcC4+Neslz5qn7x+W3pQ1Bmz5\/JFLc+HJZzGdvlfC10jlwNezWcYQFPuVBdDPoWvNQZHsV26AfobGrNmvPIB++jZUVQLViUzQT99aZS+w2q\/cNLSisG9FWNuvnAj99I0nkJdC98jszVQKfD2bsfkKGgw1CdMkoNorGF+r\/coPIg\/uqPY0L0tUWDD10h0NpygRHverINoGodM\/+GFaqP5muHMB1WbvVzCI4zCl2pz9Crggoab2w3T3q22a2PGWavP2KycFcEd\/i9iA0HUFsgL1bideGgZss71fOfE2jXdss7NfeWnkphbb7O5XYLeL0pRt9var1IUh1VwX5WsK8hx160aut7XER\/Z+Ffi+H0keOfvVzgvdJBIfuftV7EZB6oiPvP0KpnBHD6PM8BBC4APHYptttBw7htpQs4MwDSCFJ9zsInoFbuSwzd5+hcgFDl2eUNIaa7\/yItvxLLbZ3q92sbP1bLbZ2a+SyAcOZJtdhFXgeQHbjJCdwACwCMCI9nx\/G7PNCMnRzu2KvnbNmMZiDwZss7tfJQEM0y3bjLrE\/wzNTVlB1GcSAtcHXLuNMB4A1+Hanf3KAa5FbXrS7iJK3iZbj2v39qvAS4J42Al1jZEbpJELAdOKCDnxafpGrajHwIldl2l10fi8gB5fTRDrhJ4\/YPCYg7omVUdta0P+Z30JwzXDoMpXtjCp51PPn98F9nMCf4X7lR2jn4FvlKBu2EK8mCceT02N1xY4gBpZ+8Der7auG2xT\/oGDiNt3Ap9\/gIjK3wEv5B+QNbbB8OAFHjEhAw84MdOKiCoNU89nWvHOidIAMK3ufoX2+NZmWr39apdCi+rteLngeSZMb6jV3q981Bvb6uxXgROFFM2gVhfzrRRYTCvqLYJuMrQCWLVzs1y2taNdwLSiLeowM0atCJkWCAMWAsZksqPGkFwJ2XrATV2uGfVnBZ7nsc1oAa2dFXBvu\/sVtCIr5JpRl2ESRxQyQEs2ru9bTCtGp09TGWp1ECMLvZiF4O5X0Q5Aik2gVsRngwSmNOdErvEEoY4Tcu0YpVuP3m643cHsw3Njrh2h1YtSn4ePEQtdCrFxXl4T1K+TujQc0m7vV17suz7k2hGhutsoDLl2dLo5YEdhkbR7iCsmAFL9nnLC4x1AkTtqRX2CAFCEjVodfFTvKJ6NWtGh7iQBRcKolfB3QJEaEgUJchHFs81oNeEOUKSNmxF\/DxIvAWwzwmyQuCFkm9GCWluLQniaEfaepkkQBGyzjZqBRVEsbnZQcwDchG3GFOuGLgcbr+Uu2kW0RFVWEDFBL42sIKUe1KfqGu1X8Y45l2OzBi+gKMB+lSTxjhIxYiTn1vV+FXlJuPNoIQ82RPgMnIgm9tiMq\/KCeGMUUodFbF6rCAmwabpNHVrKO5c1yOL9Cro7EFPLamaoDHWcJiGkWyOAYs72qxCGIX1ENyj1CV7bNIiY8w8\/QDLKLvL8kH\/gYM5juQIozJICyQOMcDfyII3wK8zNtKzrLCfC0BbwT4trnENQSSaKH5\/ek6qUCcfoId61Epzih68Z1gFS1C3\/LMpKvNoudeK1j46wlKwG6a4pKxQLiERUSG9W8rhsTki+34ItO02A9QY\/8QNvIMYLLC85bHk2oHh2+8AmMqUnPEA8zQrprdQ+IGeFtRUekOPCirwxnU1Wxn5QrZIwCZOYU6045QarVrwER1QrYAMbAF618qIwjgNOtYq8yIt41YqDilUrO7RDOxJVKycK4sjSV62S0I4CS6JahWAXAJdVrcLYty1OtUrCyKVEIKJagciNYla18kHkgZhVrSw7CKiTo1OtuK471WoHYwBtQbXywC5MXEG1cuwgoPrrVCsvcsEOCqrVFtgpcKSqVbKLw1SuWkXeLoJy1SpMgjSGUtUqAF5EHTG0auX5rhWKqlUUbn1Kc+lUq2QbeYGoWu3i2N8BUbVKd5Bv9pDC6idhLKhWaQJdsBVUq3QLdtS+61QriAT9VFCtotABbiyoVn5qB9TR26lW8S6JYSqoVjs3iqEjqFZ+tPPjVFCtnDTYctounmXkMmpLp1pxFN2rVhxV96oVjGGQxKJqxVF3r1pxFN6qVhxttqrVzon9BPKqFYSpnXq8apV6wA8F1Spy7JAyzFCqleNbm+7fae3KdjjtCiYwofYA0a7iXbyjVqDVrrb21t7KtCsnsmMPSLQrH0l4UKJdgdBz\/VSiXcE4pOmK0q4i6IaA165SB8I44rWrOEhiSkjrtKs4ioIdr125Xgi9lNeurMSnLU2tdgVB6tB8nWhXIEicEPDalR+COAC8duW4oRVEvHZlOx6kzupWu0qj1E18XrtKnTihRO9Ou0p3obfjtasoCCwH8NrVNnRdOxC0qzSAu8QWtCsYxP5uK2pXyS70E0G7AlYQuDtBuwo8N7ZTXruCKUxSn9euYi9KqH3Yalc7Owxji9eu\/NS3djGvXbmeY\/upqF2laRrEsahdpUmShqGoXaVh5FJI7bUr6G6hsxO1q8jyAvrg7rSr1Et9yibUa1dI8qBOvV67QnJC7IvaVRjtPFoH6rSrwAp2262gXXmW7Xu8duVGvhNGgnZl72zqpGi1Kx\/Gu8CRaFdbR9SunNiFFIhOu3LTbRr5gnYVprFNGU177cqKA2omnXYVe77rRqJ2FcQeddh02hVMQ9oG0mlXyc6nN0OnXQGLMSR12pUfM0anQbuyoyBygahdgSAEgSfTrjgVpNeudnFsM6J0r125aZjuUkG7gsEutSxRu0p8HzLtnXYVx9sdddK32hXcQZi6Eu0qDmMn8iTa1S6N4limXaVO4mzBHO2KW4VBuwKu49ij2lUAPeB6o9qVMFFau7KsrRM5I9qVgFNKu7KsHdy6Uu0qjIPEtaXalbAarHa1jYI0GtOudvgfQbuCXhLHiUS7SpPUojjIoF2lQbzbRRLtCoY7+uAdtKvY94EbSbQrpCs6rnDFT9Ld1THSrlB5hOOpGb38a1UwlDDjtwb2WwP7rYH91sB+a2C\/NbDfGthvDey3BvZbA\/utgf3WwH5rYJMa2IhD8+v5ZqL3caJukjQUixH7OAfny2cfBzhug5fTZhcgD82DJGhVw2\/69bxPr3lexxWExa3twrasl9NQzua9LWczFgbW1Udc4EUqThW5b6LpbmKQx58\/42JopmE7IQKAkqgaf+Aij+v1OOZQaPMRysJ4uxgSMnw02bVQXkU+z06zXc8NaF4Ss9uU1\/jUZrTuCqm0WcaPFYjYFOOHDG058ir5FU5ghg\/vK986kdbAtSpxPh8Lh51xAWcTgNtaCWcSGdiXLtEruiIASSpwFGCg+UdZcRwH0nk6i7VA+EKciLioGoPWJ67+4HgfRVnHVXZpxusV9xSGqHpNioH41icqRp4JUB3L6jEZjfp67vFVQZC8M5Vq6ZHqBMAj\/gSK0WwMRPlXPM3hERZJPf7CJSvGHzajOe8RRWVFcxvbmVhrG2qMoteSqryYaZYjC0+UX6vPttWVXaQfGfSzu6s1kQrgw26yUAuOemSGSx5PhOZPEbibfCiJ91R1LhP49clJBpLq+t8s+BbHANWaxMjBcYUx6I7gmJcR5D++Yf6X5TjeSVlZSzkjNzHLIn9fOJT2a93d2aJPtfB9dSNbPNlaBmzCF1g0tV5ns0qJdV+N80WLqR1K5SSeyNEri8mzJfGexNi7lmcuxBy135sWyj3MfIlsx+uNcPYxT2zZkwl0zMUhZsIyHPaL6xM04hDqIe7+0AkZSCTsWIBrodOF6Xks8YM+75reKXgOX5\/KCywGcicTY5JQTGCB+YMOtZmT73oyKcdkquKlh3M7blxQ6DHJzEImaN5pKxTjJDF28Mhs6hzS5YKLK+bXDizrMD3Vbi6KY668Fo2QgBHn37nkCC0sQErbwGkGOs6B\/6AyVQbSfLSHu8rrqQkOIWRx+vR+FVDhWziLgZCU64IahxpIbVAzgifwkqFptarbgCivoymEPqGQaXPKxg9LE+HxMmSowokdDEe11viLNuyvB\/CYzFEdOI6Muz3T58\/vVk+eMH5+FhrM+991iwfh7BdcyRWcI8OS1v1hxLse0VsuFbE1Reh0ic6sOMEqa\/DUh7\/4Aj8HbV0OT54kWplIIDMFg9FWxzWELOazACsUFdAgo6Pm2yhQ\/ln35fIy730UIR41j0m0rWCmJxg\/94mKAjpRUTDkre222qAKod1wR+nasYWvr1UKYrieyDSGM1eitAaybNKofYJ0pJVUWZSMpIKmOf\/k0TBmQGHES2rWE6MmsfyyMjF6Kbl6OENiM+a05otfCNxuHlZTkNeQ1vDelWU6qDQbmplKeqB1Fd9EXi3W8ljErJuyzGsqrSI+HZAILM\/cwHw2V74vLzdNCQnx\/5+TvEZm6iSFue1hn+OKH1ytQtHQON1Zn2ahl1Kfng4Kfa+tidsqfiEtmomimD3KNGaVLiLDRVleJjXRpQPS1gDagXQVxyaw1mLLDLoKwqY\/qHJiKmButMjCOMlzlcx9zrReQE7nZnFn1yIimQCV6Ywp+QOj5i5JGrP8wV4Kkqwc6msLmPyptIIq1XOPUs8rarm00i+OMgMmXxqumwTees6H70va65IQl7gRJH9BjFdv+BpSbIpJfO8wdNjLD3hQXBX45RsYyXP6hTkE1Zkv2EETaneQdlNgk65aywRo5THHytcd\/QfC8aUvX2NxV0e8XmpmRh2Qox6+XUCRDBLURuMbvnz9REGOhQoCRkKXPvM2kVyzQy0K0r7mjbCQ6m6M+uU4LkDLc3eT5J1qQbWGxxlZWdnswPeVnfFVokUNj0gtuX8DdiyDOWcDzf3mau+35aVyBFuNxNKMMwtq32IS1DEE49MEo4P4dmt\/zLZp+9DbqYyha0oXmp7Xx+\/WridNBRzVtf5g7TspGRldlBdcUVru64nqGlNt\/lTzGFPxtrUUH37FJeoDjHZoWWoJZ0Tp5ey2vLbkbLcGsedNJfYozaDqUd3IMDCUeYXDtjQPDFm7tG3dX0TsgaIJohTZHZo2F8TbqpVP5DaWMTvS0mvxU3aRyys3Vb0vChsfw2zRuMwKnEeFaVqYkNxOuGq7XnYx69cR0DZ9EUIRWA\/bmYQ92JDUBqJeq6pfvz5V4BVhnUIYWmBQDZWobddP4HFD8x\/korneiA5XSxwzpgbYwAqFsUwNMrSEQWYNO0Ycr\/SoMbJuNMoTI2D0yu6wGJTAP5BhYz3cAVsydZFyg0NOdp4lVRuVF0Yzr4baqc01mIGmqbKoZbxWx\/8Ztk\/l0XQ9wc9qZm0C3kKqEjk5LlmdQU55XrQihcKAmKENJjlRVNdFaPp9rQtEARvUQopXG7aPLu1H61h3eoSiDGc7LJyds7tRzMF4Ek7creaY1F0yyj99pRtywg1u4HRpNejWM2UhYYzcC9L2qRa\/0waqGYWPu9snlTMrwU03LeNeO+8DjLy4hPUvsfLiweoZehcPStskSgbTZHJhnwwipKy51Hh8Zee9VjTV93NRRqN9hypDMlO50gzuNC07I4blaSmO3MzemK3OWguM3SxBWfd6Ultevr\/OTah2NdK\/YUeokivxGneWk\/eeKkPA1KgoNZ\/V43+qPXzVRnVCnYgSe39qWa2Vz6Zvfdqg\/6xlNcl2SBPm\/T7I1eg8B0k04rmSTJNdJhz72i2K5JmW+dKyDQ6EODC+NViwl41cUOiECkisw5\/XImaWwx+a0QIkmCf+JBbcpQbfeDWkeoDU+nc99hJK3ft45Rbi724yZYSxfUCrZmlAH+qMzVd18d+OaFB2MPPr2YJm8ZEW0LN6Ys8LyqYv9qNE43lRj+fl9tjbwguqva3kR1WHyO6y1qf9brn6Rlbnqonbma35RWkRvmTFbAfirJD5nE4QnsTPbNpNE3XFutZ52N\/vnl2NYMYnUDU9zEBN9vUFVM+jRhAqBKJXaDW1MwzYJHV1cM0YzFeF6jRdihKhHs2XcAp2Gi+EHHQtCahPoKrQxD3DneoPaag3oRtaoeU6knTj6HTzOtILJU7pFe8ZlgFE0so9C+5+duotl8PjjS0Yjc9F25n4aHBhRRAeZgvP4ZEY4kacsKW3WJwNQw39DBvA+MYSMfvDvK1Qn8gmyiCMWEkZX0RrAuFmfY0WnK6sxmyNeAEvPqzagX1D5Xf2Oegqy99+lVyC+o9AxTPEbtlCqQv8JDjKceZ8QUZeZEDdTNu9pd8pDa87we5KEhqtxTZb0uZI2lxJm7dez510l3loycSHb2dOfkittJa32yPtzki7O9K+BCFltgwZ+Lu5iMDJndZimy1pcyRtrqRtwaRRVqYlkybfzZw0SS+1FttsSZsjaXMlbQtJfynZLyJ5GbnLSF1G5jISXzRplJVq0azJh3OnTZJsrSWNtqzRkTW6ssYFc\/+xZN4\/Zs\/5h2mtUXyQ9YlrtlHB2E+GJzxw1qjRCIQH7ho1GqHwwFujxvmrXy\/a5vizuStfC5sc5zgTmxyxyRWbFqw3yQm2ZMLdlzPn3CU6W8tabWmrI211pa0LUPACj0vmjz+bOXmcaG0tNNlikyM2uWLTgtkeL5cls8WfzZwtTvS2FppssckRm1yxacFsAayWzBZ\/NnO2ONHcWmiyxSZHbHLFpgWzRRnilkyXfDdzviTV3VpssyVtjqTNlbQtIWiwiH3hz+YSNBAYF86zJzY5YpMrNi0SvXNQLZO98YezhW+c7m8tabRljY6s0ZU1Lpg7zt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:where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n2lhg8kq.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"dag\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>G-P01 \u00b7 EVIDENCE \u00b7 methods<\/strong>GCRI dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GCRI<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Systemic Risk Management<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">In development<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Methods and uncertainty<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Methods and uncertainty<\/h1><p class=\"nx-tagline\">The methods Systemic Risk Management relies on, the assumptions they carry and the limits of what they can show.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/risk-management\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/risk-management\/research\/\">Back to Research and evidence<\/a><\/div><dl class=\"nx-facts\"><div><dt class=\"nx-eyebrow\">Publisher<\/dt><dd>The Global Centre for Risk and Innovation<\/dd><\/div><div><dt class=\"nx-eyebrow\">Field<\/dt><dd>Risk management and systemic risk, Methods and modelling<\/dd><\/div><\/dl><\/div><div class=\"nx-hero-canvas\" data-lv-fill=\"dag\" data-lv-id=\"systemic-cascade\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Canvas<\/strong> \u00b7 draft to published version<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-g-p01-research-methods-source-passport-t nx-dag-g-p01-research-methods-source-passport-d\" 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id=\"nx-dag-g-p01-research-methods-source-passport-t\">Methods and uncertainty: from a source to a labelled evidence record<\/title><desc id=\"nx-dag-g-p01-research-methods-source-passport-d\">A source is registered with its licence and steward, checked for quality and coverage, labelled by evidence class, versioned and published with a passport; corrections create a new version. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig.<\/strong><span>How a finding is reviewed before it is published. Design, not a record.<\/span><\/p><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-sec-field\"><span>02<\/span>Hazards and exposure in Asia<\/a><a href=\"#nx-sec-methods\"><span>03<\/span>The methods in use<\/a><a href=\"#nx-sec-pg-method-register\"><span>04<\/span>Each method, its role in this field\u2026<\/a><a href=\"#nx-sec-pg-uncertainty\"><span>05<\/span>Where uncertainty in risk management\u2026<\/a><a href=\"#nx-sec-uncertainty\"><span>06<\/span>How uncertainty is reported<\/a><a href=\"#nx-sec-terms\"><span>07<\/span>Terms used on this page<\/a><a href=\"#nx-sec-pg-sources\"><span>08<\/span>Where this page's references lead<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"risk\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">The Systemic Risk Management methods page sets out the methods the platform relies on, among them decision analysis under uncertainty, scenario design and stress testing, and probability and statistics, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.<\/p><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"search\" data-nxf-kind=\"search\" data-nxf-resource=\"nexus:\/\/gcri\/G-P01\/research\/methods\/#search\" data-nxf-title=\"Search publications\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Geography<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Hazards and exposure in Asia.<\/h2><p class=\"nx-lede\">For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover with true colour from NASA GIBS, framed on Asia; every other NASA layer, live feed and forecast waits in the layer list.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-cmap-field\" data-nx-map=\"ctx-field\" data-cmap=\"asia:risk\" data-ml-points=\"on\" data-ml-src=\"risk\" data-ml-plan=\"p-871dbd0a\"><div class=\"nx-wm\" data-nx-water=\"ctx-risk\" data-wm-domain=\"ctx-risk\" data-wm-tiles=\"on\" data-wm-flat=\"on\" data-wm-focus=\"25,-11,150,56\" data-ws-live=\"off\" data-claim=\"INTEGRATED\" data-wm-panel=\"closed\" data-wm-mode=\"2d\"><div class=\"nx-wm-stage\" tabindex=\"0\" role=\"application\" aria-roledescription=\"interactive map\" aria-label=\"Hazards and exposure, Asia: satellite and model layers from NASA on a 3D terrain of ASTER GDEM elevation. Arrow keys move; with Shift they turn and tilt in 3D; plus and minus zoom, 0 resets; I inspects, question mark lists the keys.\" aria-describedby=\"nx-wm-help\"><canvas class=\"nx-wm-canvas\" aria-hidden=\"true\"><\/canvas><p class=\"nx-wm-noscript\">The interactive map needs JavaScript; the layer list and sources are below.<\/p><div class=\"nx-wm-presets\" role=\"group\" aria-label=\"Quick views\"><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"true||||\" aria-pressed=\"false\">True colour<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"cover||||\" aria-pressed=\"false\">Land cover<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"flood||||\" aria-pressed=\"false\">Floods this week<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"fires||||\" aria-pressed=\"false\">Fires and flaring<\/button><\/div><div class=\"nx-wm-panel\" id=\"nx-wm-panel\" role=\"region\" aria-label=\"Map layers\"><div class=\"nx-wm-panel-head\"><p class=\"nx-wm-panel-title\">Layers <span class=\"nx-wm-count\">2<\/span><\/p><button type=\"button\" class=\"nx-wm-icon nx-wm-panel-close\" data-wm-act=\"panel\" aria-label=\"Close the layer list\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-panel-body\"><div class=\"nx-wm-group\"><p class=\"nx-wm-group-title\">Hazards and exposure, for this page<\/p><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"true\" aria-pressed=\"true\" data-wm-z=\"20\" data-wm-lag=\"1\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite image\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">True colour<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS NOAA-20 corrected reflectance \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"true\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"cover\" aria-pressed=\"true\" data-wm-z=\"21\" data-wm-lag=\"0\" data-wm-time=\"latest\" data-wm-op=\"0.7\" data-wm-short=\"Land cover\" data-wm-prov=\"NASA LP DAAC\" data-wm-kind=\"Satellite classification; latest year GIBS publishes\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Land cover type (IGBP), yearly<\/span><span class=\"nx-wm-layer-src\">NASA LP DAAC MODIS Terra and Aqua land cover (MCD12Q1) \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"cover\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"flood\" aria-pressed=\"false\" data-wm-z=\"22\" data-wm-lag=\"0\" data-wm-short=\"Flood water\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite detection; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Flood water, 3-day composite<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS Global Flood Product \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"flood\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"fires\" aria-pressed=\"false\" data-wm-z=\"23\" data-wm-lag=\"0\" data-wm-op=\"1\" data-wm-breaks=\"10,50,200\" data-wm-short=\"Fires and flares\" data-wm-prov=\"NASA LANCE FIRMS\" data-wm-kind=\"Satellite detection; clouds and overpass timing leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Active fires and thermal anomalies, last day<\/span><span class=\"nx-wm-layer-src\">NASA LANCE FIRMS VIIRS NOAA-20 375 m (FIRMS) \u00b7 <span data-wm-date=\"fires\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"fires\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"people\" aria-pressed=\"false\" data-wm-z=\"24\" data-wm-lag=\"0\" data-wm-op=\"0.8\" data-wm-short=\"Population density\" data-wm-prov=\"NASA SEDAC (CIESIN, Columbia University)\" data-wm-kind=\"Census-based estimate, static (2020)\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Population density, 2020<\/span><span class=\"nx-wm-layer-src\">NASA SEDAC (CIESIN, Columbia University) Gridded Population of the World v4.11 \u00b7 <span data-wm-date=\"people\">static<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"people\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"evi\" aria-pressed=\"false\" data-wm-z=\"25\" data-wm-lag=\"0\" data-wm-op=\"0.85\" data-wm-short=\"Vegetation (EVI)\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite index; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Enhanced vegetation index, rolling 8 days<\/span><span class=\"nx-wm-layer-src\">NASA LANCE MODIS Terra EVI \u00b7 <span data-wm-date=\"evi\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"evi\" hidden><\/div><\/div><\/div><\/div><div class=\"nx-wm-rail\" role=\"toolbar\" aria-orientation=\"vertical\" aria-label=\"Map controls\"><button type=\"button\" class=\"nx-wm-icon nx-wm-open\" data-wm-act=\"panel\" aria-controls=\"nx-wm-panel\" aria-expanded=\"false\" aria-label=\"Layers\" title=\"Layers\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 2.5l-6.5 3.5 6.5 3.5 6.5-3.5zm-6.5 6.5 6.5 3.5 6.5-3.5m-13 2.8 6.5 3.5 6.5-3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"tools\" aria-controls=\"nx-wm-menu\" aria-expanded=\"false\" aria-label=\"Expert tools\" title=\"Expert tools\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 4.5l10 0m-10 3.5 10 0m-10 3.5 10 0m-7.5-8.5 0 3m5 .5 0 3m-3.5.5 0 3\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><span class=\"nx-wm-sep\" aria-hidden=\"true\"><\/span><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"in\" aria-label=\"Zoom in\" title=\"Zoom in\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 3v10M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"out\" aria-label=\"Zoom out\" title=\"Zoom out\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"reset\" aria-label=\"Reset the view\" title=\"Reset the view\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.2 8a4.8 4.8 0 1 0 1.5-3.5M3.2 2.6v2.6h2.6\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"full\" aria-label=\"Full screen\" title=\"Full screen\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M2.5 6l0-3.5 3.5 0m7.5 3.5 0-3.5-3.5 0m-7.5 7.5 0 3.5 3.5 0m7.5-3.5 0 3.5-3.5 0\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-menu\" id=\"nx-wm-menu\" role=\"menu\" aria-label=\"Expert tools\" hidden><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"inspect\">Inspect a point<kbd>I<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"measure\">Measure distance<kbd>M<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"compare\">Compare two dates<kbd>C<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"share\">Copy a link to this view<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"png\">Export as PNG with credits<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"xt\" data-wm-xt=\"6oPh6EhWj+gDMzpLLT8H\/wVfxJakWdyAB8snze2Nado=\">More expert tools<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"keys\">Keyboard shortcuts<kbd>?<\/kbd><\/button><\/div><div class=\"nx-wm-keys\" role=\"dialog\" aria-label=\"Keyboard shortcuts\" hidden><p class=\"nx-wm-keys-title\">Keyboard, with the map focused<\/p><dl class=\"nx-wm-keys-list\"><\/dl><button type=\"button\" class=\"nx-wm-icon nx-wm-keys-close\" data-wm-tool=\"keys\" aria-label=\"Close the shortcuts\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><p class=\"nx-wm-hint\" hidden>Hold Ctrl or \u2318 and scroll to zoom<\/p><p class=\"nx-wm-toolbar\" role=\"status\" hidden><\/p><div class=\"nx-wm-tip\" role=\"tooltip\" hidden><\/div><div class=\"nx-wm-pin\" hidden><div class=\"nx-wm-pin-head\"><p class=\"nx-wm-pin-title\"><\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"unpin\" aria-label=\"Close the card\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-pin-chart\"><\/div><div class=\"nx-wm-pin-body\"><\/div><\/div><div class=\"nx-wm-dock\"><div class=\"nx-wm-time\" role=\"group\" aria-label=\"Imagery date\"><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"prev\" aria-label=\"One day earlier\">\u2039<\/button><p class=\"nx-wm-time-label\">Latest available<\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"next\" aria-label=\"One day later\">\u203a<\/button><span class=\"nx-wm-track\" role=\"slider\" tabindex=\"0\" aria-label=\"Imagery date, up to 30 days back\"><\/span><button type=\"button\" class=\"nx-wm-latest\" data-wm-step=\"latest\" aria-pressed=\"true\">Latest<\/button><\/div><div class=\"nx-wm-chips\" role=\"group\" aria-label=\"Legends\"><\/div><p class=\"nx-wm-attrib\">NASA GIBS \/ EOSDIS \u00b7 ASTER GDEM (METI, NASA) \u00b7 Blue Marble (NASA) \u00b7 \u00a9 OpenStreetMap contributors (ODbL) \u00b7 Natural Earth<\/p><div class=\"nx-wm-legends\" aria-live=\"polite\" hidden><\/div><\/div><\/div><div class=\"nx-container nx-wm-below\"><p class=\"nx-wm-status\" role=\"status\">Loading the latest NASA imagery.<\/p><p id=\"nx-wm-help\" class=\"nx-wm-help\">Drag to move. Ctrl or \u2318 and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.<\/p><p class=\"nx-caption\"><span>For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover with true colour from NASA GIBS, framed on Asia; every other NASA layer, live feed and forecast waits in the layer list.<\/span><span data-honesty=\"true\">Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.<\/span><\/p><details class=\"nx-wm-credits\"><summary><span class=\"nx-wm-credits-line\">Data: NASA GIBS \u00b7 ASTER GDEM \u00b7 Blue Marble \u00b7 \u00a9 OpenStreetMap contributors \u00b7 Natural Earth \u00b7 Copernicus Sentinel-2 L2A \u00b7 NASA HLS S30<\/span><span class=\"nx-wm-credits-more\">Sources and licences<\/span><\/summary><p class=\"nx-wm-credit\"><ul class=\"nx-wm-credit-list\"><li data-wm-credit=\"nasa.gibs.field-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.gibs.water-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.lance.viirs-water\">VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.modis-viirs.land\">MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.lance.firms\">NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"sedac.gpw-v4\">Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" rel=\"noopener\" target=\"_blank\">CC BY 4.0<\/a><\/li><li data-wm-credit=\"nasa-meti.aster-gdem-v3\">ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"naturalearth.all-scales\">Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. <a class=\"nx-link\" href=\"https:\/\/www.naturalearthdata.com\/about\/terms-of-use\/\" rel=\"noopener\" target=\"_blank\">Public domain<\/a><\/li><li data-wm-credit=\"nasa.gibs.reference-osm\">\u00a9 OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.openstreetmap.org\/copyright\" rel=\"noopener\" target=\"_blank\">ODbL<\/a><\/li><li data-wm-credit=\"nasa.earth-observatory.blue-marble\">Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li>Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, \u00a9 OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.<\/li><li>Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, \u00a9 MapLibre contributors.<\/li><li>Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer<\/li><li>Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).<\/li><li>Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.<\/li><\/ul><p class=\"nx-wm-credit\"><strong>Layers and dates<\/strong><\/p><ul class=\"nx-wm-credit-list\"><li>True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/li><li>Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/li><li>Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/li><li>Active fires and thermal anomalies, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS \u00b7 <span data-wm-date=\"fires\">13 Oct 2026<\/span><\/li><li>Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 \u00b7 <span data-wm-date=\"people\">static<\/span><\/li><li>Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE \u00b7 <span data-wm-date=\"evi\">13 Oct 2026<\/span><\/li><\/ul><\/p><\/details><\/div><\/div><div class=\"nx-live-slot nx-live-slot--map\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gcri\/G-P01\/research\/methods\/#map\" data-nxf-title=\"Systemic Risk Management live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"risk\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">The methods in use.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/decision-analysis\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Decision analysis under uncertainty<\/span><span class=\"nx-mledger-role\">Multi-criteria treatment choice \u00b7 Decision trees for contingent plans<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/decision-analysis\/\" aria-label=\"Decision analysis under uncertainty: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/scenario-stress\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Scenario design and stress testing<\/span><span class=\"nx-mledger-role\">Cross-sector scenario design \u00b7 Reverse stress testing \u00b7 Second-round effects<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/scenario-stress\/\" aria-label=\"Scenario design and stress testing: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/probability-statistics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Probability and statistics<\/span><span class=\"nx-mledger-role\">Frequency and severity modelling \u00b7 Dependence between risks \u00b7 Combining data and judgement<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/probability-statistics\/\" aria-label=\"Probability and statistics: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/network-science\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Network science and contagion<\/span><span class=\"nx-mledger-role\">Dependency network mapping \u00b7 Centrality and concentration \u00b7 Failure propagation simulation<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/network-science\/\" aria-label=\"Network science and contagion: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/resilience-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">05<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Reliability and resilience engineering<\/span><span class=\"nx-mledger-role\">Redundancy and diversity design \u00b7 Graceful degradation planning \u00b7 Recovery time analysis<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/engineering\/resilience-engineering\/\" aria-label=\"Reliability and resilience engineering: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/risk-management\/stem\/uncertainty-quantification\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">06<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Uncertainty quantification and model validation<\/span><span class=\"nx-mledger-role\">Propagating input uncertainty \u00b7 Separating kinds of uncertainty \u00b7 Deep uncertainty framing<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\" aria-label=\"Uncertainty quantification and model validation: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><\/div><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G-P01\/research\/methods\/#evidence\" data-nxf-title=\"Evidence records\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-sec-pg-method-register\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Method register<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Each method, its role in this field and how it is checked.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><ul class=\"nx-dir\" data-cols=\"3\" aria-label=\"Method\"><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/decision-analysis\/\"><span class=\"nx-dir-name\">Decision analysis<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Decision analysis structures choices under uncertainty: it makes the options, objectives, uncertainties and trade-offs explicit so that a decision can be examined and defended.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Sensitivity to weights; Value of information; Requisite model review<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/scenario-stress\/\"><span class=\"nx-dir-name\">Scenario stress<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Scenario design and stress testing are the method this platform stewards for the network.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Plausibility review; Severity benchmarking; Model coverage<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/probability-statistics\/\"><span class=\"nx-dir-name\">Probability statistics<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Probability and statistics give risk assessment its estimates of frequency, severity and their uncertainty.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Goodness of fit; Back-testing; Prior sensitivity<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/network-science\/\"><span class=\"nx-dir-name\">Network science<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Network science represents systems as nodes and links so that the structure of dependence can be measured.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Missing link sensitivity; Validation against past events; Alternative failure rules<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/resilience-engineering\/\"><span class=\"nx-dir-name\">Resilience engineering<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Reliability and resilience engineering supply the design methods that keep systems working through failure: redundancy, diversity, graceful degradation and recovery planning.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Common-cause analysis; Exercise verification; Failure mode review<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/risk-management\/stem\/uncertainty-quantification\/\"><span class=\"nx-dir-name\">Uncertainty quantification<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Uncertainty quantification states how much a risk estimate could differ from reality and why.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Global sensitivity analysis; Calibration of intervals; Structural uncertainty<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-uncertainty\" class=\"nx-section\" data-hue=\"risk\" data-variant=\"split\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Uncertainty<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Where uncertainty in risk management analysis comes from, and how it is shown.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th>Source<\/th><th>Why it matters here<\/th><th>How it is reported<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">Likelihood estimates<\/td><td data-label=\"Why it matters here\">Often expert judgement on rare events<\/td><td data-label=\"How it is reported\">Calibrated language and the basis of each estimate<\/td><\/tr><tr><td data-label=\"Source\">Consequence estimates<\/td><td data-label=\"Why it matters here\">Depend on cascade assumptions<\/td><td data-label=\"How it is reported\">Ranges with dependency assumptions stated<\/td><\/tr><tr><td data-label=\"Source\">Risk matrices<\/td><td data-label=\"Why it matters here\">Can rank risks inconsistently<\/td><td data-label=\"How it is reported\">Matrices supplemented with distributions where data allow<\/td><\/tr><tr><td data-label=\"Source\">Velocity and onset<\/td><td data-label=\"Why it matters here\">Rarely estimated, yet decisive for response<\/td><td data-label=\"How it is reported\">Explicit onset and duration fields<\/td><\/tr><\/tbody><\/table><\/div><p class=\"nx-p\">Heat maps are used as communication devices, not as analysis; the underlying estimates are published with them.<\/p><\/div><\/div><\/section><section id=\"nx-sec-uncertainty\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Uncertainty<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">How uncertainty is reported.<\/h2><\/div><div class=\"nx-section-body\"><ol class=\"nx-rows\"><li><span class=\"nx-eyebrow nx-index\">01<\/span><div><h3 class=\"nx-h4\">State assumptions<\/h3><p class=\"nx-p nx-mt-1\">Each analysis lists its assumptions and the data it depends on.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Quantify where possible<\/h3><p class=\"nx-p nx-mt-1\">Ranges and confidence are reported alongside central estimates.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Validate and compare<\/h3><p class=\"nx-p nx-mt-1\">Models are checked against observations and, where possible, against other models.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Publish limits<\/h3><p class=\"nx-p nx-mt-1\">What an analysis cannot show is stated beside what it can.<\/p><\/div><\/li><\/ol><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Uncertainty quantification<\/td><td data-label=\"Definition\">Characterising and propagating the uncertainties in a model to state confidence in its outputs.<\/td><\/tr><tr><td data-label=\"Term\">Sensitivity analysis<\/td><td data-label=\"Definition\">Repeating an analysis under different assumptions to show how much the result depends on them.<\/td><\/tr><tr><td data-label=\"Term\">Model validation<\/td><td data-label=\"Definition\">Comparing model predictions with independent observations to judge fitness for a stated use.<\/td><\/tr><tr><td data-label=\"Term\">Decision analysis under uncertainty<\/td><td data-label=\"Definition\">Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-sources\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Where this page's references lead.<\/h2><p class=\"nx-lede\">The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.<\/p><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/www.iso.org\/standard\/65694.html\" target=\"_blank\" rel=\"noopener\"><span>ISO 31000:2018 Risk management, guidelines (ISO)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.iso.org\/standard\/72140.html\" target=\"_blank\" rel=\"noopener\"><span>IEC 31010:2019 Risk assessment techniques (ISO\/IEC)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.coso.org\/enterprise-risk-management\" target=\"_blank\" rel=\"noopener\"><span>COSO Enterprise Risk Management framework<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.epfl.ch\/research\/domains\/irgc\/\" target=\"_blank\" rel=\"noopener\"><span>IRGC risk governance framework (EPFL International Risk Governance Center)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-10-sec\" class=\"nx-section\" data-hue=\"risk\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>Are the methods open?<\/summary><div class=\"nx-answer\">Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-11\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-11\" class=\"nx-h3 nx-mt-2\">Around Systemic Risk Management.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/therisk.global\/risk-management\/research\/sources\/\">Source and data register <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/risk-management\/\">Systemic Risk Management home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/risk-management\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/\">The Global Centre for Risk and Innovation home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/trust\/\">GCRI governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-12\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Systemic Risk Management<\/span><h2 id=\"nx-close-12\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"mailto:contact@therisk.global?subject=Systemic%20Risk%20Management%3A%20Methods%20and%20uncertainty\">Write to the team <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/risk-management\/contact\/\">See all contact routes<\/a><\/div><\/div><\/section><\/div><\/div><script class=\"_iub_cs_skip\">window.__nxMount ? window.__nxMount(document.currentScript) : null;<\/script>\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"FAQPage\",\"@id\":\"https:\/\/therisk.global\/risk-management\/research\/methods\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/therisk.global\/risk-management\/research\/methods\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Are the methods open?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Method descriptions are public on the STEM Commons. 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