{"version":"1.0","provider_name":"\u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","provider_url":"http:\/\/www.geology.com.ua\/en","author_name":"\u0410\u0434\u043c\u0456\u043d\u0456\u0441\u0442\u0440\u0430\u0442\u043e\u0440","author_url":"http:\/\/www.geology.com.ua\/en\/blog\/author\/andriy\/","title":"Geoinformatika 2017; 1(61) : 63-71 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"ZSBbz9hobq\"><a href=\"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-161-63-71\/\">Geoinformatika 2017; 1(61) : 63-71<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-161-63-71\/embed\/#?secret=ZSBbz9hobq\" width=\"600\" height=\"338\" title=\"&#8220;Geoinformatika 2017; 1(61) : 63-71&#8221; &#8212; \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\" data-secret=\"ZSBbz9hobq\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=http:\/\/www.geology.com.ua\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","description":"Geoinformatika 2017; 1(61) : 63-71\u00a0(in Russian)\u00a0 AUTO-CALIBRATION OF STREAMFLOW IN A SMALL RIVER CATCHMENT WITHIN SWAT-CUP V.V. Osypov, N.N. Osadcha Ukrainian Hydrometeorological Institute, 37, Nauki Ave., Kyiv, 03028, Ukraine, e-mail: valery_osipov@ukr.net Purpose. The implementation of process-based SWAT model (Soil and Water Assessment Tool) to simulate streamflow in the territory of Ukraine. Comparison of different auto-calibration procedures of SWAT-CUP software for SWAT input parameters calibration. Design\/methodology\/approach. The model was applied in a small Holovesnya catchment on the territory of the Desna water-balance station. 18 parameters were used for runoff calibration after the analysis of sensitivity. This parameter set was calibrated using four auto-calibration procedures available in SWAT-CUP: SUFI-2 (Sequential Uncertainty Fitting), PSO (Particle Swarm Optimization), GLUE (generalized likelihood uncertainty estimation), ParaSol (Parameter Solution). The Nash\u2013Sutcliffe coefficient (NS), coefficient of determination (R2) and percentage of bias (PBIAS) were used to assess the model performance. Findings. The model was calibrated against measured daily runoff of Holovesnya in 2007 and 2009. According to the common performance ratings of calibration efficiency, all SWAT-CUP procedures showed good close results. More detailed comparative analysis of the SWAT parameter values showed that the best results were obtained using SUFI-2 (NS = 0.68, R2 = 0.68, PBIAS = -1.6). Practical value\/implications. The successful implementation of SWAT was achieved for streamflow calibration in a small river catchment. The detailed analysis of the auto-calibration procedures of SWAT-CUP was carried out. In general, all methods of calibration of process-based models, including SWAT, use inverse modeling approach, which is associated with the inability to directly measure the majority of input parameters used in the model. The main disadvantage of this approach is the non-uniqueness of solutions, i.e. the existence of different parameter sets that satisfy the specified value of the objective function. In order to minimize this problem, there is a necessity for additional measurements, such as snow melt, flow above the gauge, etc. Keywords: SWAT, SWAT-CUP, Inverse modeling, streamflow. The full text of papers"}